Latest on Forbes
The invisible economy
Your next biggest customer may not be human.
When AI agents become the buyer, brands will compete on value machines can verify. What happens to personalization, loyalty, and the customer journey?
Read the essayThe notebook of Himanshu Sinha
Building AI.
Thinking out loud.
I build enterprise AI—and write about the decisions, trade-offs, and emerging ideas that shape it.
Personalization AI agents Trust & safety
AI leader. Author. Hands-on builder.
Marriott International · Founder, PlainThinkMore from my desk
Essays & field notesAgent sandboxing becomes a policy teams can review.
A closer look at Microsoft MXC and the boundaries we set for AI agents.
The hidden cost of a misspelled prompt.
How small input errors can become an overlooked cost of running AI at scale.
Better explanations. Better decisions.
Closing the gap between what a model predicts and what business leaders can trust.
Close to the technology.
Closer to the problem.
I’m a data scientist who likes getting things into the real world. At Marriott International, I lead advanced data science work in personalization and customer decisioning. Before that, I worked on retail analytics at CVS Health and data observability at Precisely.
That experience shapes what I write about: how AI changes customer behavior, what makes a model useful, and how to build systems people can understand and trust.
Through PlainThink, I help teams put AI to work. At AI Safety & Security, I explore the practical questions behind safer agents. I’m also a Forbes Technology Council member and the author of Approach (Almost) Every Business Problem with AI.
Outside the day job, I mentor with SCORE and ADPList.Let’s talk
Now
What I’m building
Work
Featured case studies
- 01Targeting & PersonalizationOne-to-one guest relationships, with Adobe and Marriott.
- 02Scalable Forecasting & PricingPersonalization engines at retail scale.
- 03AI-Driven Data ObservabilityIntegrity and quality when data starts to drift.
- 04Fraud / Churn PredictionPropensity scoring for telecommunications marketing.
Experience
A timeline of enterprise AI
Apr 2023 – PresentRemote / HQ
Director – Advanced Data Science
Marriott International
Leading AI/ML transformation for growth decisioning.
May 2022 – Apr 2023Remote / HQ
Lead Data Scientist
CVS Health
Driving high-performance personalization engines at scale.
Apr 2012 – May 2022Naperville, IL
Data Scientist, Emerging Tech
Precisely Inc. (formerly Infogix)
Pioneering data observability and integrity with ML.
Prior to 2012Global
Analytics & Data Engineering Leadership
Wipro / Others
Foundational work in predictive analytics and ETL.
Writing
Publications and thought leadership
Books, research papers, and technical articles.
- Approach (Almost) Every Business Problem with AIBook · Amazon
- An Efficient Machine Learning Based Models for Anomaly Detection in Network TrafficResearch · IEEE
- Analysis of anomaly and novelty detection in time series data using machine learning techniquesResearch · MSJ
- The Identification of Network Intrusions with Generative Artificial Intelligence Approach for CybersecurityResearch · JoWACS
- Benchmarking Predictive Performance Of Machine Learning Approaches For Accurate Prediction Of Boston House Prices: An In-Depth AnalysisResearch · IJARISE
- Generative Adversarial Networks for Improving Detection of Network Intrusions in IoT EnvironmentsResearch · IEEE
- Automated Image Identification and Classification of Tiger Beetles Based on Deep Learning ModelResearch · IEEE
- A Sentiment Analysis of Product Review Data Through Large Language Models (LLMs)Research · IEEE
- The Ultimate Blueprint for Enterprise Chatbots: Simplify, Scale, SucceedArticle · TechBullion
- Typos are no longer innocent: How a misspelled word quietly inflates your AI billArticle · Medium
- 5 signs your company is falling for 'AI-generated strategy' — and what to do insteadArticle · Medium
- The Time Deposit Method: How I Broke Free From Digital Addiction and Reclaimed My LifeArticle · Medium
- Spot the Red Flags: 3 Signs Your Young Team Members Are Falling BehindArticle · Medium
- Mastering Image Segmentation with Python: A Step-by-Step Guide to Build a U-Net ModelGuide · Medium
- How to Build a Proactive Data Drift Detection Platform with AIGuide · Medium
- AI-Powered Credit Card Recommendation Chatbot: How Generative AI is Transforming PersonalizationCase Study · Medium
Awards
Recognition
- International Hackathon – Bronze MedalNOAA & KaggleAwarded for detecting illegal fishing boats via satellite imagery classification.
- Best Paper AwardIEEE ConferenceAwarded Best Paper at an IEEE-organized conference held at a leading engineering institute.
- Best Paper AwardIEEE ConferenceAwarded Best Paper at an IEEE-organized conference held at a leading engineering institute.
- Global Leadership RecognitionMarriott InternationalAwarded for exceptional leadership and strategic impact in global technology operations.
Media
Featured writing and interviews
- Forbes Technology CouncilThe Invisible Economy: Your Next Biggest Customer May Not Be HumanAug 21, 2026 · Article
- Forbes Technology CouncilThe Hidden AI Cost Few Leaders Track: How Typos Inflate Your LLM SpendJan 16, 2026 · Article
- Forbes Technology CouncilAI Bridges The Trust Gap: How Explainable AI Aligns Modelers And Business LeadersFeb 19, 2025 · Article
- TechBullionFrom AI Visionary to Industry Leader: Himanshu Sinha on Transforming Enterprises with Machine Learning and Generative AI2024 · Interview
Skills
Core competencies
AI/ML Leadership & Strategy
- Enterprise ML portfolio leadership
- AI strategy and roadmap
- Stakeholder alignment
- Governance and risk
- Prioritization
ML Productization & MLOps
- Productionization
- Monitoring and observability
- Model drift and evaluation
- Scalable rollout
- Spark and Python pipelines
Personalization & Optimization
- Decisioning systems
- Uplift modeling and experimentation
- Recommendation engines
- Customer value modeling
- Acquisition optimization
Observability & Anomaly Detection
- Proactive data observability
- Novelty detection
- Metadata profiling
- Enterprise data integrity
Fraud & Customer Analytics
- Churn and retention modeling
- Fraud detection
- Behavioral prediction
- Multi-market deployments
GenAI Strategy & Adoption
- Use-case design
- Evaluation strategy
- Guardrails and safety
- Cost and quality tradeoffs
- Enterprise adoption
Technical Core: GenAI & DL
- Transformers (BERT, GPT)
- GANs and VAEs
- Multi-agent systems
- Reinforcement learning
- CNNs and LSTMs
Technical Core: Engineering
- Apache Spark and Hadoop
- Python (Pandas, PyTorch)
- SQL and distributed computing
- AWS, GCP, and Azure ML
- MLOps pipelines
Education
Degrees
M.S., Business Analytics
Indiana University, Kelley School of Business · 2016
M.B.A., Finance
Madurai Kamaraj University
B.C.A., Computer Applications
Indira Gandhi National Open University (IGNOU)